The present invention is directed to methods and systems for detecting bias, falsehoods, and manipulation in social media content, and for filtering out unwanted content to improve accuracy of social media content and the analysis of social media content.
Online social networks connect billions of people across the world. Every day, users upload millions of posts including text, audio, video, images, links, and much more. Additionally, users of these social media sites are typically free to comment on the posts of other people.
To improve the user's experience and to provide targeted advertising, content analysis software can perform semantic analysis of social networking content and provide various different types of services including advertisements, recommendations, customer behavior analysis, and more.
However, much of the content posted on social networks is manipulated, unduly biased, and/or artificial. These unwanted posts can have serious negative consequences for software analyzing social media content to provide targeted advertisements, recommendations, and customer behavior analysis.
For example, images can be staged, misleading, or unfairly biased. While posting a photo on a social network, the user will often select a photograph where the user looks especially good, or where the photograph was staged to project a visual of how the user wants to be perceived. As another example, a group of people may visit a location but due to bad weather they could not go outside, so they capture an indoor party photograph and share with a social network indicating that they are “feeling excited” when in fact they are disappointed that they can't be outside.
Social media content can also be unduly biased. Bias can come from past experience, things learned from others, relationships, and from many other sources. Often, people will provide comments that other people want to hear rather than what they truly think, which is a form of manipulation of the comment author's true sentiment.
Reputation can also be manipulated. Different people have different reputations in society or their community, and in order to give more value to users who have a good or desirable reputation level, social media posts and comments may be manipulated according to the reputation of the person on whose post the author is leaving a comment. For example, a comment author may not express his true feelings because he understands the reputation of the author of the social media content.
Another possible influencing factor for manipulating social media content is pop culture status. For example, users of a social media platform may provide overly positive or overly negative comments about a highly popular pop culture icon or trend due to the overwhelming ubiquity of the icon or trend.
Another problem with social media is fake or anonymous accounts. For example, most celebrities, companies, and organizations have social network accounts with more than one person posting comments using the same account. In this case multiple users are updating and providing comments on-behalf of the celebrities, companies, organizations. Further, many accounts are created as phishing accounts using fake or stolen identities.
Accordingly, there is a continued need in the art for systems and methods that identify and filter social media content and comments which are biased, false, or otherwise manipulated.